Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Friday, July 4, 2014

Decision Support for Stroke Rehabilitation Therapy via Describable Attribute-based Decision Trees

Does your therapist have an objective decision tree for how they approach your therapy? Or are they enamored of 'All strokes are different, all stroke recoveries are different'?
http://www.public.asu.edu/~pturaga/papers/StrokeDecisionTree.pdf
Vinay Venkataraman, Pavan Turaga, Nicole Lehrer, Michael Baran, Thanassis Rikakis, and Steven L. Wolf
Abstract
—This paper proposes a computational framework
for movement quality assessment using a decision tree model
that can potentially assist a physical therapist in a telereha-
bilitation context. Using a dataset of key kinematic attributes
collected from eight stroke survivors, we demonstrate that the
framework can be reliably used for movement quality assess-
ment of a reach-to-grasp cone task, an activity commonly used
in upper extremity stroke rehabilitation therapy. The proposed
framework is capable of providing movement quality scores that
are highly correlated to the ratings provided by therapists, who
used a custom rating rubric created by rehabilitation experts.
Our hypothesis is that a decision tree model could be easily
utilized by therapists as a potential assistive tool, especially in
evaluating movement quality on a large-scale dataset collected
during unsupervised rehabilitation (e.g., training at the home),
thereby reducing the time and cost of rehabilitation treatment.
 
6 more pages and some great math equations.

1 comment:

  1. I can pretty much guarantee that your therapist has no objective decision making tree and if any therapist out there uses one, I'd like to meet that person.

    ReplyDelete